""" Maple code printer The MapleCodePrinter converts single SymPy expressions into single Maple expressions, using the functions defined in the Maple objects where possible. FIXME: This module is still under actively developed. Some functions may be not completed. """ from sympy.core import S from sympy.core.numbers import Integer, IntegerConstant, equal_valued from sympy.printing.codeprinter import CodePrinter from sympy.printing.precedence import precedence, PRECEDENCE import sympy _known_func_same_name = ( 'sin', 'cos', 'tan', 'sec', 'csc', 'cot', 'sinh', 'cosh', 'tanh', 'sech', 'csch', 'coth', 'exp', 'floor', 'factorial', 'bernoulli', 'euler', 'fibonacci', 'gcd', 'lcm', 'conjugate', 'Ci', 'Chi', 'Ei', 'Li', 'Si', 'Shi', 'erf', 'erfc', 'harmonic', 'LambertW', 'sqrt', # For automatic rewrites ) known_functions = { # SymPy -> Maple 'Abs': 'abs', 'log': 'ln', 'asin': 'arcsin', 'acos': 'arccos', 'atan': 'arctan', 'asec': 'arcsec', 'acsc': 'arccsc', 'acot': 'arccot', 'asinh': 'arcsinh', 'acosh': 'arccosh', 'atanh': 'arctanh', 'asech': 'arcsech', 'acsch': 'arccsch', 'acoth': 'arccoth', 'ceiling': 'ceil', 'Max' : 'max', 'Min' : 'min', 'factorial2': 'doublefactorial', 'RisingFactorial': 'pochhammer', 'besseli': 'BesselI', 'besselj': 'BesselJ', 'besselk': 'BesselK', 'bessely': 'BesselY', 'hankelh1': 'HankelH1', 'hankelh2': 'HankelH2', 'airyai': 'AiryAi', 'airybi': 'AiryBi', 'appellf1': 'AppellF1', 'fresnelc': 'FresnelC', 'fresnels': 'FresnelS', 'lerchphi' : 'LerchPhi', } for _func in _known_func_same_name: known_functions[_func] = _func number_symbols = { # SymPy -> Maple S.Pi: 'Pi', S.Exp1: 'exp(1)', S.Catalan: 'Catalan', S.EulerGamma: 'gamma', S.GoldenRatio: '(1/2 + (1/2)*sqrt(5))' } spec_relational_ops = { # SymPy -> Maple '==': '=', '!=': '<>' } not_supported_symbol = [ S.ComplexInfinity ] class MapleCodePrinter(CodePrinter): """ Printer which converts a SymPy expression into a maple code. """ printmethod = "_maple" language = "maple" _default_settings = { 'order': None, 'full_prec': 'auto', 'human': True, 'inline': True, 'allow_unknown_functions': True, } def __init__(self, settings=None): if settings is None: settings = {} super().__init__(settings) self.known_functions = dict(known_functions) userfuncs = settings.get('user_functions', {}) self.known_functions.update(userfuncs) def _get_statement(self, codestring): return "%s;" % codestring def _get_comment(self, text): return "# {}".format(text) def _declare_number_const(self, name, value): return "{} := {};".format(name, value.evalf(self._settings['precision'])) def _format_code(self, lines): return lines def _print_tuple(self, expr): return self._print(list(expr)) def _print_Tuple(self, expr): return self._print(list(expr)) def _print_Assignment(self, expr): lhs = self._print(expr.lhs) rhs = self._print(expr.rhs) return "{lhs} := {rhs}".format(lhs=lhs, rhs=rhs) def _print_Pow(self, expr, **kwargs): PREC = precedence(expr) if equal_valued(expr.exp, -1): return '1/%s' % (self.parenthesize(expr.base, PREC)) elif equal_valued(expr.exp, 0.5): return 'sqrt(%s)' % self._print(expr.base) elif equal_valued(expr.exp, -0.5): return '1/sqrt(%s)' % self._print(expr.base) else: return '{base}^{exp}'.format( base=self.parenthesize(expr.base, PREC), exp=self.parenthesize(expr.exp, PREC)) def _print_Piecewise(self, expr): if (expr.args[-1].cond is not True) and (expr.args[-1].cond != S.BooleanTrue): # We need the last conditional to be a True, otherwise the resulting # function may not return a result. raise ValueError("All Piecewise expressions must contain an " "(expr, True) statement to be used as a default " "condition. Without one, the generated " "expression may not evaluate to anything under " "some condition.") _coup_list = [ ("{c}, {e}".format(c=self._print(c), e=self._print(e)) if c is not True and c is not S.BooleanTrue else "{e}".format( e=self._print(e))) for e, c in expr.args] _inbrace = ', '.join(_coup_list) return 'piecewise({_inbrace})'.format(_inbrace=_inbrace) def _print_Rational(self, expr): p, q = int(expr.p), int(expr.q) return "{p}/{q}".format(p=str(p), q=str(q)) def _print_Relational(self, expr): PREC=precedence(expr) lhs_code = self.parenthesize(expr.lhs, PREC) rhs_code = self.parenthesize(expr.rhs, PREC) op = expr.rel_op if op in spec_relational_ops: op = spec_relational_ops[op] return "{lhs} {rel_op} {rhs}".format(lhs=lhs_code, rel_op=op, rhs=rhs_code) def _print_NumberSymbol(self, expr): return number_symbols[expr] def _print_NegativeInfinity(self, expr): return '-infinity' def _print_Infinity(self, expr): return 'infinity' def _print_Idx(self, expr): return self._print(expr.label) def _print_BooleanTrue(self, expr): return "true" def _print_BooleanFalse(self, expr): return "false" def _print_bool(self, expr): return 'true' if expr else 'false' def _print_NaN(self, expr): return 'undefined' def _get_matrix(self, expr, sparse=False): if S.Zero in expr.shape: _strM = 'Matrix([], storage = {storage})'.format( storage='sparse' if sparse else 'rectangular') else: _strM = 'Matrix({list}, storage = {storage})'.format( list=self._print(expr.tolist()), storage='sparse' if sparse else 'rectangular') return _strM def _print_MatrixElement(self, expr): return "{parent}[{i_maple}, {j_maple}]".format( parent=self.parenthesize(expr.parent, PRECEDENCE["Atom"], strict=True), i_maple=self._print(expr.i + 1), j_maple=self._print(expr.j + 1)) def _print_MatrixBase(self, expr): return self._get_matrix(expr, sparse=False) def _print_SparseRepMatrix(self, expr): return self._get_matrix(expr, sparse=True) def _print_Identity(self, expr): if isinstance(expr.rows, (Integer, IntegerConstant)): return self._print(sympy.SparseMatrix(expr)) else: return "Matrix({var_size}, shape = identity)".format(var_size=self._print(expr.rows)) def _print_MatMul(self, expr): PREC=precedence(expr) _fact_list = list(expr.args) _const = None if not isinstance(_fact_list[0], (sympy.MatrixBase, sympy.MatrixExpr, sympy.MatrixSlice, sympy.MatrixSymbol)): _const, _fact_list = _fact_list[0], _fact_list[1:] if _const is None or _const == 1: return '.'.join(self.parenthesize(_m, PREC) for _m in _fact_list) else: return '{c}*{m}'.format(c=_const, m='.'.join(self.parenthesize(_m, PREC) for _m in _fact_list)) def _print_MatPow(self, expr): # This function requires LinearAlgebra Function in Maple return 'MatrixPower({A}, {n})'.format(A=self._print(expr.base), n=self._print(expr.exp)) def _print_HadamardProduct(self, expr): PREC = precedence(expr) _fact_list = list(expr.args) return '*'.join(self.parenthesize(_m, PREC) for _m in _fact_list) def _print_Derivative(self, expr): _f, (_var, _order) = expr.args if _order != 1: _second_arg = '{var}${order}'.format(var=self._print(_var), order=self._print(_order)) else: _second_arg = '{var}'.format(var=self._print(_var)) return 'diff({func_expr}, {sec_arg})'.format(func_expr=self._print(_f), sec_arg=_second_arg) def maple_code(expr, assign_to=None, **settings): r"""Converts ``expr`` to a string of Maple code. Parameters ========== expr : Expr A SymPy expression to be converted. assign_to : optional When given, the argument is used as the name of the variable to which the expression is assigned. Can be a string, ``Symbol``, ``MatrixSymbol``, or ``Indexed`` type. This can be helpful for expressions that generate multi-line statements. precision : integer, optional The precision for numbers such as pi [default=16]. user_functions : dict, optional A dictionary where keys are ``FunctionClass`` instances and values are their string representations. Alternatively, the dictionary value can be a list of tuples i.e. [(argument_test, cfunction_string)]. See below for examples. human : bool, optional If True, the result is a single string that may contain some constant declarations for the number symbols. If False, the same information is returned in a tuple of (symbols_to_declare, not_supported_functions, code_text). [default=True]. contract: bool, optional If True, ``Indexed`` instances are assumed to obey tensor contraction rules and the corresponding nested loops over indices are generated. Setting contract=False will not generate loops, instead the user is responsible to provide values for the indices in the code. [default=True]. inline: bool, optional If True, we try to create single-statement code instead of multiple statements. [default=True]. """ return MapleCodePrinter(settings).doprint(expr, assign_to) def print_maple_code(expr, **settings): """Prints the Maple representation of the given expression. See :func:`maple_code` for the meaning of the optional arguments. Examples ======== >>> from sympy import print_maple_code, symbols >>> x, y = symbols('x y') >>> print_maple_code(x, assign_to=y) y := x """ print(maple_code(expr, **settings))